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Collection, as the first stage of the recycling process, and pre-processing to increase waste stream purity constitute key operations for achieving high recycling rates and a closed loop in the circular economy. For wastepaper recycling in Hong Kong, it is the semi-formal-informal recycling (SFIR) sector that plays a central role in both stages. This study analyses the so far little explored SFIR stakeholder network in Hong Kong and sheds light on value chains, recovered waste paper quantities and the impact of policies on the sector. The findings show that SFIR stakeholders reclaim 55.6 t/recycling station/month of wastepaper and thereby achieve about a 5.7 times higher reclaim rate than the formal-private recycling system. Critical to this achievement is the SFIR transaction network, which enables its stakeholders to develop a value chain and thereby generate an added value of around 1900 HKD (243.9 USD/t) for wastepaper. Given limited circular structures in Hong Kong, financial subsidies are critical to sustain the SFIR's operations over the short-term. However, over the long-term legalization and integration of its stakeholders are necessary to ensure an economically and socially sustainable wastepaper recovery system in Hong Kong. [Display omitted] • Qualitative & quantitative analysis of the semi-formal-informal recycling (SFIR) sector. • The SFIR's wastepaper value chain achieves a cumulative added value of 1900 HKD/t. • The SFIR recovered 5.7 times higher capacities than the formal system in 2021. • Financial support can enhance the SFIR sector's recovery capacities. [ABSTRACT FROM AUTHOR]

The current paper replicates findings related to the analytical heuristic of 'metalinguistic density'. It provides updated theoretical motivations for an analytical focus on explicit metalanguage in online text-based settings, based on notions of symbolic interactionism. An analysis of online user comment data of the 2019 Hong Kong protests reconfirms that the relative occurrence of metalanguage focusing on certain terms indicates the extent to which these terms' denotational norms are shared amongst a community of language users. While most terms in the corpus do not regularly attract explicit metalanguage, several terms thematically related to the protests did. This disproportionate metalinguistic attention may be explained by political disputes on the movement's legitimacy, which led to normative debates on the discursive representation of the protest movement. Finally, certain phrases had become indexical of a certain political position to the extent that they were the frequent target of irony. In general, the results suggests that 'metalinguistic density' is a useful heuristic to employ in text-analytical investigations that seek to explain participants' interpretations of discursive interactions. • 'Metalinguistic density' measures the sharedness of terms' denotations. • Results of earlier research are replicated in a thematically distinct dataset. • Metalanguage reflects ideological clashes over discursive representation. [ABSTRACT FROM AUTHOR]

• This study compared drivers of the same ethnic group driving across within-country borders. • The existing theoretical framework of cross-border risky behavior patterns has been expanded. • Gender, age, illumination, and weather do not individually affect cross-border driving risk. • Conclusions are of representative reference value for cross-border risk management policies. Introduction: Due to globalization and the acceleration of cross-border exchanges, cross-border risk behaviors have received widespread attention. Previous research has concluded that foreign cross-border drivers engage in relatively more risk-taking behavior patterns and are likely to experience a higher crash rate or be more inclined to cause severe crashes. However, there is little evidence on the comparison of drivers who belong to the same ethnic group driving across within-country borders. Method : Based on the cross-border motor-vehicle crash reports in 2006–2010 from the Road Traffic Accident Database of the China Ministry of Public Security, this paper examines the risk factors of being at fault and getting killed or seriously injured in cross-border traffic crashes and casual paths toward crash liability and injury severity for Hong Kong and Macao drivers driving in the Chinese mainland. Results : There are extremely complex factors behind drivers from Hong Kong and Macao causing at-fault crashes or sustaining fatal and serious injuries in the Chinese mainland. Factors such as gender, age, illumination, and weather conditions do not individually affect the risk of driver at-fault crashes or severe casualties in the crashes among Hong Kong and Macao drivers driving in the Chinese mainland. Nonetheless, collectively, these factors influence them along with different vehicle types, roads, and environmental factors. Conclusion s: This paper provides more theoretical findings for understanding the compound effect of multiple risk factors involving cross-border at-fault crashes or serious casualties. The conclusions of this research are valuable as representative references for cross-border risk management policies. Practical applications : To reduce the effects of different factors on cross-border risky driving behaviors and/or injurious crashes, various measures should be focused on, including specialized driver training, enhancement of the roads/environment, development of effective road safety campaigns, and directives facilitating cross-border cooperation in the field of road safety. [ABSTRACT FROM AUTHOR]

Using Hong Kong's smart city development as the case study, this paper aims to discover the influence of public trust on citizens' perception of Hong Kong's smart city performance in an international dimension, comparing with the smart city ranking by research agencies. Our central investigation further focuses on the association of public trust and digital trust, using COVID19 contact tracing app as an example. This paper uses data from a Hong Kong-based territory-wide survey in 2021 to conduct the analysis. The result suggests a positive relationship between public trust, subjective perception and digital trust, and supports that public acceptability is a cornerstone of an effective public policy. [ABSTRACT FROM AUTHOR]

In recent years, promoting regional synergistic development has become the shared objective in city-regions during the new stages of development. This paper aims to uncover the dynamics of synergistic development in urban agglomerations by constructing an index measurement system based on four dimensions: industrial synergy, innovation synergy, infrastructure synergy, and institutional synergy. By comprehensively employing theories and methods such as "space of flow" big data analysis, network analysis, and interlocking network models, this study examines patterns and capacities of synergistic development in the Guangdong-Hong Kong-Macao Greater Bay Area. The main instances of industrial cooperation between cities are observed in Hong Kong-Shenzhen and Guangzhou-Shenzhen; capital flows primarily concentrate in Guangzhou-Shenzhen and Hong Kong-Shenzhen. Research paper and patent collaborations between cities are predominantly concentrated in Hong Kong-Shenzhen; joint laboratories are mainly established in Hong Kong-Macao and Hong Kong-Guangzhou; inter-city co-construction of higher education institutions is mainly focused on Guangzhou-Foshan and Shenzhen-Hong Kong. Infrastructure synergistic development performs best in Guangzhou-Shenzhen, Guangzhou-Foshan, and Shenzhen-Dongguan. Cross-border collaboration benefits from institutional advantages held by Hong Kong and Macao. Urban interactions with outstanding performance include Guangzhou-Shenzhen, Hong Kong-Shenzhen, Guangzhou-Foshan, Shenzhen-Dongguan. Additionally, increasing interaction trends can be observed between Guangzhou-Dongguan as well as Shenzhen-Zhuhai/Shenzen-Foshan partnerships. Understanding the typical characteristics and potential trends of synergetic development within the GBA holds significant practical value for establishing a first-class bay area along with a world-class urban agglomeration. • Concept and connotation of synergistic development in urban agglomeration area was examined. • Indicators and methods for evaluation of synergistic development in the GBA were conducted. • Patterns and capacities of synergistic development at urban scale in the GBA were explained. • Urban interaction with highest synergistic development level is Guangzhou-Shenzhen. [ABSTRACT FROM AUTHOR]

Digital storytelling, an innovative way of writing, has been introduced to young learners who are taught to construct stories with digital tools to convey their knowledge and ideas. In 2018 and 2019, 31 digital stories created by Hong Kong primary school students were published on a digital story writing platform and linked from an online gamified reading platform. Each book on average gained 4,000+ views from across the globe and received 3,000+ favorable comments in total. While the digital stories are popular in these platforms, their quality and education value are uncertain. A review of the literature shows there is a lack of robust tools for assessing digital stories by young authors. The research team for this paper thus constructed their own framework in evaluating digital stories. An assessment of the stories has been done by two capable assessors, who found that the stories overall were of good quality and suggested room for improvement. This paper made three contributions: (1) "invention" of a digital story assessment framework; (2) it shows that stories created by students (with support from educators) can be an enjoyable and useful educational resource for their peers; and (3) digital storytelling can help foster the development of young authors. [ABSTRACT FROM AUTHOR]

• An optimal width allocation policy for traffic lanes and footpaths is developed. • Optimal lane width is 5.4 m when user and agency costs are equally important. • Hong Kong road agency places a higher weight on each dollar of user cost. • Allocation to footpaths can reflect the importance placed on pedestrian safety. Introduction: Walkability continues to attract great attention from urban planners, designers, and engineers as they recognize not only the merits of pedestrian facilities in terms of the health benefits but also their demerits in terms of accident risk to pedestrians. Wide footpaths improve the pedestrian environment and experience, and thereby motivate travelers to walk as much as possible. However, if footpaths are too wide, they may leave a smaller space for the roadway. On the other hand, wide road lanes may lead to higher road vehicle safety but are costly to construct and maintain and also may leave little space for the footpath. Evidently, for a fixed urban space, what is needed is an optimal balance between the vehicle lane and pedestrian path. This problem is encountered routinely in dense cities including Hong Kong where land availability is severely limited. Method: To address the issue, this paper first establishes safety performance functions (SPFs) for the pedestrian space and the road space, using the random-parameter negative binomial regression. The results indicate the extent to which road lane and footpath width changes are associated with changes in in-vehicle occupant and pedestrian casualties. Then the paper uses the SPFs to develop a methodology for optimizing the width allocations to the road lanes and footpaths, duly considering the user (safety) costs and agency (construction) costs associated with each candidate allocation of the widths. Finally, the paper analyzes the sensitivity of the optimal solution to the relative weights of user cost and agency cost. Results: When user and agency costs are considered equally important, the optimal lane width is 5.4 m. Conclusion: It is observed that the road space allocation ratio used by the Hong Kong road agency suggests that the agency places a higher weight to user cost compared to agency cost. Practical Application: The findings can help incorporate design-safety relationships, and the stakeholders (agency and users) perspectives in urban road and footpath design. [ABSTRACT FROM AUTHOR]

In this paper, we estimate the energy efficiency of educational buildings with the case study of buildings in City University of Hong Kong by constructing an energy demand stochastic frontier model. The model is estimated by using the university statistical data from 2011 to 2015. For the consistent frequency of data among the variables, we have adopted the quadratic-match sum method to convert annual university report data into a monthly dataset. Our result shows the average energy efficiency is 0.87, implying that 13% of total energy consumption can be saved. We then calculate how much of the energy saving potential has been achieved by constructing the performance score, which increases from 0.08 to 0.17. It implies that the campus performs more efficiently in saving energy over time. We further develop econometric decomposition analysis based on the energy demand frontier model to identify the factors affecting energy consumption. It suggests that research activities account for a large share of overall energy consumption. Analysis on energy end-use shows university should improve efficiency in lab instrument as it is least efficient among the four usages. We expect this paper can provide the fundamental and methodological guideline for university-scale energy efficiency estimation. • Estimating energy efficiency of educational buildings needs to consider the composition of research related factors. • Energy efficiency of campus building presents increasing tendency with seasonal cycle over time. • Research related variables affect significantly on energy efficiency of educational buildings. • Energy use in lab instrument needs to be effectively managed to save energy. [ABSTRACT FROM AUTHOR]

• Automatic MiC envelopes and layout generation by a novel SSG-MOO method. • Multi-objective optimization formulation for passive MiC design. • A pilot MiC study in Hong Kong produced 5 selected Pareto optima out of 625. • Up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement against the baseline. • A multi-level analysis of results and design strategies for practitioners. Modular-integrated Construction (MiC) is an emerging construction technique promoted in the building sector for high productivity and low waste emission in the construction phase; yet, the standardized modules also bring new challenges, such as balancing passive energy efficiency and spatial daylight autonomy, to the operational phase. This paper proposes a Symmetric Skeleton Grammar-based Multi-Objective Optimization (SSG-MOO) method to formulate parametric MiC envelopes and detailed layout, with the two objective functions being energy efficiency and interior daylight performance in the operational phase. Pareto optima of the SSG-MOO, computed by the Non-dominated Sorting Genetic Algorithm II, are generally verified and analyzed in three levels, i.e., MOO's solution space, SSG layout, and MiC design parameters. A case study of MiC residential building in Hong Kong demonstrated the SSG-MOO method through five new passive MiC designs (i.e., spatial reorganization of three architectural modules, and parameter tuning of the envelops and corridors), achieving up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement compared to the baseline design. The contribution of this paper is two-fold, including a novel and sound SSG-MOO formulation for parametric MiC designs, and offering time-efficient and evidence-based design tactics for MiC designers and industrial practitioners to push boundaries of MiC. [ABSTRACT FROM AUTHOR]

With the launch of the Shanghai-Hong Kong and the Shenzhen-Hong Kong Stock Connect programs, the correlations among the three stock markets have been more complex. Therefore, this paper applies the Minimum Spanning Tree and Sliding Window methods to analyze the complex correlations of the 38 financial institutions in the three markets. Based on closing prices ranging from January 1, 2011 to December 31, 2021, three conclusions are obtained. The top 20 institutions in the network were mainly banking institutions from 2011 to 2013, while the node strength of non-banking financial institutions tended to increase from 2014 to 2021. The network shows different structures over time, even the changes in the three correlation coefficients generally show the same trend. The degree correlation between any two layers is positive, but the similarity shows different characteristics. These results would help to enrich multi-layer network theory and reveal the evolutionary characteristics of the correlation between financial institutions. [ABSTRACT FROM AUTHOR]

• A comprehensive analysis of root causes for the accelerated internal corrosion in steel saltwater pipes coated with fusion bonded epoxy. • Cathodic delamination of the epoxy lining is identified as the primary cause of early internal corrosion failure. • Dynamic cyclic load has a greater chance for crack propagation in the epoxy lining compared to static load. • Development of recommendations and precautions based on the results of failure analysis. Effective functioning of saltwater supply system is essential to Hong Kong government agencies. However, it has been frequently observed that steel saltwater pipes suffered from severe internal corrosion and consequently early burst accidents, which may cause high economic loss and safety concerns to the public. Therefore, by taking a sample saltwater pipe made of DN450 mild steel with internal and external walls coated with fusion bonded epoxy in Hong Kong, this paper investigates the root causes and failure mechanism for the internal corrosion of this failed steel saltwater pipe through laboratory experiments and numerical simulation analysis. Two hypotheses are proposed and validated: (1) cathodic delamination of the epoxy lining, and (2) delamination of the epoxy lining due to external mechanical loads. The results verify that the sample saltwater pipe failed due to the cathodic delamination of the epoxy lining, and the electrochemical corrosion of the inner pipe wall. Moreover, it can be concluded that external mechanical load has few significant impacts on the damage of the epoxy lining for this sample pipe. This study exemplifies the importance of an in-depth analysis on the internal corrosion of steel water pipes, especially in a highly-corrosive internal environment. [ABSTRACT FROM AUTHOR]

• This paper focuses on daily natural gas consumption forecasting. • A novel hybrid model is developed for daily natural gas consumption forecasting. • The most recent datasets of four cities in three climate zones are collected. • An improved singular spectrum analysis is first proposed. In daily natural gas consumption forecasting, the accuracy of forecasting models is vulnerably affected by the noise data in historical time series. Singular spectrum analysis (SSA) is often introduced into hybrid models for denoising. However, as a deterministic-based algorithm, SSA does not give good results when a time series is contaminated with a high noise level. Considering this fact, this paper proposes an improved SSA (ISSA) that modifies the determination method of subseries selection in the reconstruction stage of SSA. Combining ISSA with long short-term memory (LSTM), a novel hybrid model, ISSA-LSTM, is thus developed. Additionally, for validating the robustness and superiority of ISSA-LSTM, the historical datasets of four representative cities located in three climate zones are collected as the training and testing datasets, and a comparison of ISSA-LSTM with five advanced models is performed. The results reveal that SSA would generate negative values when time series close to zero and the contribution of SSA in improving the forecasting accuracy of LSTM is insignificant. In contrast, ISSA avoids generating negative values and reduces the mean absolute range normalized error (MARNE) of LSTM by a range of 0.86–11.86%. Among the models, ISSA-LSTM achieves the best performance and its MARNEs for London (temperate zone), Melbourne (subtropical zone), Karditsa (subtropical zone), and Hong Kong (tropical zone) are 4.68%, 5.72%, 5.76%, and 14.10%, respectively. The MARNE of the tropical city is higher than that of others, which is caused by the complex natural gas consumption pattern of itself. [ABSTRACT FROM AUTHOR]

• Applying InVEST model to determine ecological sources. • Building ecological resistance surfaces for highly urbanized region. • Proposing a local evaluation model for ecological networks. • Summarizing the ecological network development suggestions. Metropolitan regions usually encounter sustainability difficulties such as overexploitation of resources, severe land scarcity, and ecological degradation, resulting in the progressive collapse of ecological networks (ENs). It is therefore essential to strengthen the construction and protection of ENs by integrating various resources, improving the quality of the urban ecological environment and creating a favourable living environment. Using the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, in this paper, the ecological resistance indicator system that balances natural condition and human disturbance is rebuilt. In doing so, a construction scheme (applicable to highly urbanised areas) is established to simulate ENs at a more precise scale. Moreover, a local evaluation model of ENs is proposed and the spatial patterns of multiple indicators are fully summarised. The findings show that the ENs of the Guangdong-Hong Kong-Macao Greater Bay Area exhibit apparent spatial disparity. Disturbance through human activities seriously affects the spatial pattern of ENs, leading to structural imbalance and quality impairment of ecological corridors. Based on our assessment, the construction of complementary ecological corridors in the "two green belts" planning of the Guangdong-Hong Kong-Macao Greater Bay Area will improve structural problems. The findings of this paper can provide a reference to the harmonisation of urban development and ecological protection, by guiding the scientific management of ecological spaces in highly urbanised regions. [ABSTRACT FROM AUTHOR]

Buildings are responsible for about 92% of the total energy end-use in Hong Kong, of which above 70% is from the commercial sector. Most of the buildings in Hong Kong are high-rise, and approximately 15% of the total building stock is commercial buildings. Despite the considerable improvement in the understanding of the life cycle energy use of office buildings, there is still a lack of research into the life cycle energy demand of high-rise office buildings. Such knowledge is however essential for facilitating building energy conservation in the high-rise urban environment. The aim of this paper is to investigate the life cycle energy use of high-rise office buildings. The research was carried out through a critical literature review and case studies of ten real-life high-rise office buildings in Hong Kong. Results show that the life cycle energy consumption is 51.78–73.64 GJ/m 2 over the 50-year study period. Building operation consumes 78–89% and the rest (i.e. 11–22%) is taken by the embodied energy. Despite the distinction in terms of the amount of embodied energy between high-rise buildings and low-rise counterparts, no clear correlation is found between building height and embodied energy intensity. Moreover, energy use for material manufacturing and transport should be prioritised in reducing the embodied energy, of which the transport energy needs to be taken into extra consideration for the case of Hong Kong. The findings should inform construction industry participants of the significant potential in reducing the embodied energy of high-rise office buildings. The paper profiles the life cycle energy use of high-rise office buildings and should be important for the policy formulation towards the holistic energy conservation in high-rise buildings over their lifespans. [ABSTRACT FROM AUTHOR]

The construction of an ecological security pattern (ESP) is an important undertaking in ensuring the stability of the ecosystem and the long-term growth of humanity. Existing research, However, existing research often overlooks the quantification of policy implications in ESP development. The objective of this paper was to bridge this gap by integrating policy quantification analysis (PQA) with nature, society and into ESP construction and providing targeted ecological management recommendations. The policy texts were quantified into reusable research data, which served as a foundation for the selection of indicators and the optimization of ecological security patterns, by using machine learning techniques. The methodology "Patch-matrix-corridor" was used to create a spatially correlated ecological security pattern. Through factor analysis and Random Forest (RF), the impact of each indicator on ecological security was thoroughly examined, offering substantial support for policy development and ESP construction planning. The Guangdong-Hong Kong-Macao Greater Bay Area(GBA) was selected as the study area, the study found that: (1) The proposed framework PQA based-ESP could provide a useful eco-management tools. (2) Policy adaptability had a substantial impact on environmental security in the GBA, but the ecosystem service index has the highest impact. (3) Applying the framework, we identified a total of 1,993 km2 of ecological sources, 23 key ecological corridors, 58 general ecological corridors, and 31 ecological nodes. An improved ESP, characterized as "one circle, two bays, three rivers, multiple areas, corridors, and nodes," was constructed in the GBA. (4) Given the multi-scale analysis, tailored ecological management policy recommendations were proposed for each city in the GBA. The study's findings offer actionable solutions for the international community facing growing ecological challenges. [ABSTRACT FROM AUTHOR]

Radiative cooling coating technology is gaining increasing attention in the context of mitigating urban heat island and tackling global climate change. This paper is concerned with the development of an inorganic geopolymer-based radiative cooling coating using red mud, incorporating varying sizes of TiO 2 and hollow glass beads. The developed colored coating demonstrates its radiative cooling capability in reducing the surface temperature by harnessing the potential of red mud. The physico-chemical properties, surface morphology, and element distribution of the coating were characterized by XRD, FTIR, TG-DAT, SEM and EDS. The coating exhibited lower UV (0.0844) and visible reflectance (0.5275) but high NIR reflectance (0.7536), as well as high infrared emissivity of 0.9455, enabling a red color with a CIE value of L* = 74.56, a* = 9.55, and b* = 11.98, and a maximum temperature reduction of 7.3 °C under the climate of Hong Kong. Additionally, the skid resistance, abrasive resistance and adhesion strength of the proposed coating could meet the requirements of standards, indicating a great potential for footway applications. [ABSTRACT FROM AUTHOR]

Electricity consumption in cities is steadily increasing. Using a life cycle approach and fuel mix data from power companies’ sustainability reports, this paper analyzes greenhouse gas (GHG) emissions from electricity consumption in Hong Kong. The results show that coal contributed on an average 74.3 percent, liquefied natural gas 25.1 percent, and oil 0.6 percent of the thermal energy consumed for generating electricity in Hong Kong between 2002 and 2015. Besides, Hong Kong imported an average of 7.96 billion kWh per year net electricity from a nuclear power plant in Shenzhen. During this period, GHG emissions from annual electricity consumption ranged between 27.0 and 34.1 million tons (MT) and the emission factor ranged between 702 and 792 g CO 2 -eq/kWh. Hong Kong’s gross domestic product (GDP) increased steadily from USD 176 billion in 2002 to USD 297 billion by 2015. As a result, Hong Kong’s electricity productivity increased from 4.62 to 6.75 USD/kWh while GHG emission from electricity consumption per GDP decreased from 0.153 to 0.104 MT CO 2 -eq/USD billion. Hong Kong’s annual electricity consumption was predicted over the short-term period (2016–2020) and medium term (up to year 2030). Electricity consumption is likely to increase to 44.63 billion kWh by 2030 while GHG emissions from electricity consumption would increase to 33.92 MT of CO 2 -eq. The implications are discussed at the end of the paper. [ABSTRACT FROM AUTHOR]

Public play spaces are designed for children to develop their social and physical abilities and enrich their experience. Through play, children can learn various cognitive skills in a relaxing environment. All children should have the same right to play in play spaces. However, many existing playgrounds lack inclusive facilities to facilitate the needs of the disabled children. This paper takes Hong Kong as a case study. In our preliminary observation there is no disabled children playing or even appeared in nearly all of the play spaces. The current design of the playgrounds also does not take the needs of children's care takers into consideration. This results in misusing playground facilities by the care takers. In order to address the issue of inclusive play for children and the care takers, the paper reviews the playgrounds in Hong Kong in terms of the accessibility and availability and identifies the inclusive issues in playgrounds of the densely populated city. It also highlights the current strategies that the government has developed to deal with the problem. The paper argues that in a populous city such as Hong Kong it is inevitable to encounter difficulties in building inclusive play spaces and promoting inclusive play, and specific strategies of using spaces creatively is a must to ensure an effective design for children's play in needs. [ABSTRACT FROM AUTHOR]

Rapid design and construction of mobile cabin hospitals (MCHs) have become imperative in the COVID-19 response. However, due to unique design specifications (e.g., parallel design and model pre-revision), collaboration in emergency construction projects (ECPs) like MCHs presents data security vulnerabilities, including a lack of traceability and transparency. These hazards invariably reduce design effectiveness, leading to undesirable rework and project delay. Blockchain technology is a potential solution to address the aforementioned security issues in ECPs because it offers immutable and traceable data storage. Nevertheless, directly implementing blockchain in ECPs is impractical, for the blockchain has a complex deployment process and provides limited functions supporting BIM-based design. Therefore, this paper develops a lightweight blockchain-as-a-service (LBaaS) prototype to enhance the ECPs design efficiency by securing and automating information exchange while eliminating the difficulties of deploying and using blockchain. This paper contributes three elements: (1) Security vulnerabilities of design in ECP are identified. Taking an MCH in Hong Kong as an example, this paper investigates its design process and determines two design characteristics and associated security flaws. (2) Key technologies to support easy deployment and usage of blockchain in ECPs are developed. New technical elements, including a Multi-to-One mapping (MtOM) kit for easy blockchain registration, an integrated workflow retaining existing design practices, and smart contracts for secure interaction with blockchain, are developed to support LBaaS functionality. (3) An LBaaS prototype is validated and evaluated. The prototype is illustrated and evaluated using design examples based on actual MCH project data. Results show that the LBaaS is a feasible and secure approach for ECPs collaboration. This paper deepens the understanding of data security issues in ECPs and offers technical guidance in establishing blockchain solutions. • Identified security vulnerabilities of BIM-based collaboration in emergency construction projects (ECPs). • Exploring the mechanism of integrating ECPs design with a lightweight blockchain-as-a-service (LBaaS). • Developed key technical elements to support functionalities of an LBaaS prototype. • Validated LBaaS prototype via three design examples from an actual mobile cabin hospital project. • Results show that the LBaaS is a practical solution for improving data security and ECP design efficiency. [ABSTRACT FROM AUTHOR]

Several frameworks are introduced to address occupancy-based building performance. However, the performance predictions obtained using these frameworks deviate from real performance. So, this study's aim is to represent a new framework for the automatic assessment of occupants' comfort and building indoor performance using BIM and the SD-ABM platform. Initially, an office space in Hong Kong, consisting of 10 occupants, was considered for the BIM model construction. The occupancy, indoor data and required equations are defined using the SD-ABM model. Essential data from the BIM model can be transferred using the Dynamo-Excel platform. Furthermore, a validation study was conducted using a paper-based survey from the occupants and sensor data for environmental data monitoring while error metrics were also calculated. The framework actively predicts occupant presence, comfort level, temperatures, and CO 2 concentration in the office space. However, a comprehensive usability and feasibility study is required to assess the efficiency of the framework. [ABSTRACT FROM AUTHOR]

Despite a rich body of research on face-work, how it is performed in online edu-social groups remains under-explored. Drawing on posts and comments of Facebook groups created for courses at a university in Hong Kong, together with interviews with students, tutors, and the lecturer, this article examines how code-switching is deployed as a powerful discursive resource in the performance of face-work. Notwithstanding English being the medium of instruction of the courses, code-switching is noticeable. Focusing on these participants' practices, our analysis discovers that code-switching serves primarily to signal the breakdown of the expectedly formal academic participation frame and the switch to an informal frame. Multiple layers of action frames are collaboratively and constantly designed and redesigned in these 'social network-educational spaces' (Chau and Lee, 2017), where the formal-informal, public-private, and academic-social boundaries become indistinct. Closer analysis within and across the spaces further reveals that norms of appropriateness of code-switching to achieve informality and solidarity may vary depending on a combination of individual, contextual, and temporal factors. In addition to contributing to existing literature on code-switching and face-work on Facebook, the article offers practical implications for understanding the increasingly informalized discourses in institutional contexts. • Code-switching is a face-work strategy to achieve informality and express solidarity in social network-educational spaces. • Norms of appropriateness of code-switching vary depending on individual, contextual, and temporal factors. • This paper contributes to the strand of literature on face-work with a focus on online discourse in a multilingual setting. [ABSTRACT FROM AUTHOR]

• Big data and artificial intelligence for air pollution monitoring and health management • Personalized and synchronized data for personalized advice and alert • Smart interventions for effecting behavioral change • Causal relationship between PM 1.0,2.5 vs FEV 1 and FVC All people in the world are entitled to enjoy a clean environment and a good quality of life. With big data and artificial intelligence technologies, it is possible to estimate personalized air pollution exposure and synchronize it with activity, health, quality of life and behavioural data, and provide real-time, personalized and interactive alert and advice to improve the health and well-being of individual citizens. In this paper, we propose an overarching framework outlining five major challenges to personalized air pollution monitoring and health management, and respective methodologies in an integrated interdisciplinary manner. First, urban air quality data is sparse, rendering it difficult to provide timely personalized alert and advice. Second, collected data, especially those involving human inputs such as health perception, are often missing and erroneous. Third, the data collected are heterogeneous, and highly complex, not easily comprehensible to facilitate individual and collective decision-making. Fourth, the causal relationships between personal air pollutants exposure (specifically, PM 2.5 and PM 1.0 and NO 2) and personal health conditions, and health-related quality of life perception, of young asthmatics and young healthy citizens in Hong Kong (HK), are yet to be established. Fifth, whether personalized and smart information and advice provided can induce behavioural change and improve health and quality of life are yet to be determined. To overcome these challenges, our first novelty is to develop an AI and big data framework to estimate and forecast air quality in high temporal-spatial resolution and real-time. Our second novelty includes the deployment of mobile pollution sensor platforms to substantially improve the accuracy of estimated and forecasted air quality data, and the collection of activity, health condition and perception data. Our third novelty is the development of visualization tools and comprehensible indexes, by correlating personal exposure with four types of personal data, to provide timely, personalized pollution, health and travel alerts and advice. Our fourth novelty is determining causal relationship, if any, between personal pollutants, PM 1.0 and PM 2.5 , NO 2 exposure and personal health condition, and personal health perception, based on a clinical experiment of 150 young asthmatics and 150 young healthy citizens in HK. Our fifth novelty is an intervention study to determine if smart information, presented via our proposed visualized platform, will induce personal behavioural change. Our novel big data AI-driven approach, when integrated with other analytical approaches, provides an integrated interdisciplinary framework for personalized air pollution monitoring and health management, easily transferrable to and applicable in other domains and countries. [ABSTRACT FROM AUTHOR]

In model updating, damage detection and structural health monitoring (SHM), modal identification is usually the first step to calculate the modal properties, such as natural frequencies, damping ratios and mode shapes, of the targeted structure utilizing the measured time-domain responses. Ambient vibration test provides an efficient and economical mean to collect structural vibration responses for the purpose of modal identification since no artificial excitation is required. This paper presents the work on the ambient vibration test and modal identification of a recently constructed boat-shaped building situated in Hong Kong. The building is not an isolated structure, and it is connected with a secondary structure in its fourth and fifth floors. To identify detail mode shapes, sixty-two measurement points were desired. They were located in the three staircases (to minimize the effect on the normal operation of the building) and on a typical floor of the building. Due to the large number of measurement points coving almost all floors of the building, multiple setups with moving references approach were designed. Some common problems encountered in the field test were discussed in this paper. A recently developed fast Bayesian FFT method was employed to perform the modal identification. This method could identify the most probable value (MPV) of modal parameters efficiently and also calculate the associated posterior uncertainty analytically, providing an important tool to evaluate the accuracy of modal parameters. The first nine modes were identified including five translational modes, two torsional modes, one combined mode and one vertical mode. Due to the connections with other building, torsional behavior was observed in some translations modes. Based on the MPV and the associated uncertainty, the variability of modal parameters across different setups is also addressed. Some interesting feathers of this structure were studied and investigated, providing the baseline for the future SHM and condition assessment of this building. [ABSTRACT FROM AUTHOR]

Hong Kong buildings account for 90% of total electricity consumption and over 60% of greenhouse gas emissions. Therefore buildings present both a challenge and an opportunity for reduction in energy use and greenhouse gas emissions. Net Zero Energy Building (NZEB) and Net Zero Carbon Building (NZCB) are recognised as feasible strategies to reduce energy use and carbon emissions leading to a more sustainable built environment. While there is a growing number of NZEBs and NZCBs in relatively cool or temperate climates, there are relatively few examples in the subtropical climate, and in a densely populated city such as Hong Kong. This paper will examine the current progress towards a low carbon built environment in Hong Kong, zero energy/carbon design strategies and technologies applicable to building in a subtropical climate, and examines a case study of Hong Kong's first zero carbon building ZCB. ZCB's energy and carbon performance, experiences and lessons learned, and future directions are discussed. The paper will conclude with the challenges and opportunities for wider adoption of NZEBs and NZCBs in the Hong Kong construction industry. [ABSTRACT FROM AUTHOR]

• An effective nested max–min ant algorithm for VRP model is proposed. • VIP priority and drop-off point has been considered. • Nested max–min ant system for VRP model considered a set of possible scenarios. • The numerical experiments show that the CPLS is implemented successfully. • The model can solve the possible scenarios within reasonable computation times. E-commerce logistics have required rapid and efficient e-fulfillment services to deliver goods to consumers within a short time window to fulfill the customer order requirement. This paper seeks to address how an E-commerce Logistics Company can utilize the Cyber-Physical Logistics System (CPLS) and Internet of Things (IoT), which may unlock the potential for solving the order assignments and the vehicle routing problems on a new twist. The CPLS allocates orders to suitable vehicles and plans the best route in order to maximize the order fulfillment rate through cloud computing to reduce local computation power. This paper presents a novel Nested MAX-MIN Ant System (MMAS) to tackle a Vehicle Routing Problem (VRP) that can serve as the core element of the CPLS. The objective is to perform to maximize the orders, minimize the total traveling cost and satisfy all the problem constraints. This paper intends to address the issues associated with the VIP priority and drop-off point limitations to make the solution route more realistic and enhance accuracy. The numerical experiences show that the CPLS is implemented successfully in a Hong Kong-based E-commerce Logistics Company with promising performance within reasonable computation times and new better solutions. [ABSTRACT FROM AUTHOR]

In practice, most of the intelligent transportation systems provide average travel times of all vehicles on selected paths in real time on a regular basis. However, path travel times of different vehicles could vary widely under different traffic conditions. There is a need to consider the differences in vehicle classes for path travel time estimation. This paper proposes a novel modeling framework that considers variance–covariance relationships between vehicle classes for real-time estimation of multi-class path travel times with use of multi-source traffic data collected from various types of sensors. The proposed methodology is examined with a case study of a selected urban expressway in Hong Kong with data obtained from multiple sources. The path travel time estimates by vehicle class are validated and the results demonstrate the merits and performance of the proposed framework. [ABSTRACT FROM AUTHOR]

Conductive hydrogels have wide use in multifunctional sensors. Nevertheless, the intrinsic features of conductive hydrogels, including the absence of sensation mechanisms with varied properties, impede their application in wearable devices. To this end, this paper fabricated a novel 3D network material, namely C/PVA/CaCl 2 /HK (CPCH) hydrogel, that comprises incorporation of graphite (C), calcium chloride (CaCl 2), hydrolyzed keratin (HK), and the polyvinyl alcohol-based (PVA-based) hydrogel. The CPCH hydrogel and the CPCH secondary hydrogel both exhibit impressive mechanical properties. The former features a maximum stress of 2.98 MPa and a maximum strain of 588 %, while the corresponding values of the latter are 1.590 MPa and 573 %, respectively. Additionally, the result showed a maximum reflected light barrier of the CPCH hydrogel at a wavelength of 248 nm. The study found that the CPCH hydrogel holds the fingers attached to the upper surface during heating for up to 10 s, demonstrating superior heat insulation performance. The gel fraction analysis revealed that the gel makes up 57.1 % of our prepared CPCH hydrogel with a porosity of 62.5 %. Besides, we conducted a conductivity test on the proposed hydrogel, obtaining a measured conductivity value of 0.04 mS/cm. Furthermore, its practicality and feasibility have been confirmed via experiments. The results show that the CPCH conductive hydrogel can potentially be a temperature-strain sensor for wearable devices. [Display omitted] • Discovering a new type of material that can be reused. • Doping graphite can significantly enhance the mechanical properties of the material. • Doping graphite enhances the hydrogel's conductivity and flexibility, thereby improving the sensor's performance. • The temperature-strain sensor made of flexible conductive hydrogel exhibits good reliability and stability. [ABSTRACT FROM AUTHOR]

This paper reports a new knowledge-driven engineered feature learning approach in response to the Global AI Challenge for Building E&M Facilities held by the Electrical and Mechanical Service Department (EMSD) of the Hong Kong SAR. The results were awarded with a Grand Prize by the competition organizer. A dynamically engineered multi-modal feature learning (DEMMFL) method is proposed for predicting the cooling load of two office buildings. The DEMMFL model is estimated with the Lasso-ridge regression and compared with other well-known methods such as the Lasso. The novel approach applies control system knowledge to engineer useful features and explore load patterns for multi-mode modeling. Deep learning methods including LSTM, GRU, and AutoGluon are implemented for automated machine learning and tested in parallel to compare the performance of the proposed model with existing methods. The proposed model is demonstrated to predict long-term cooling load most accurately using engineered features from weather information only. • A new dynamic feature engineering method for office building cooling load prediction. • Slow and fast dynamic features engineered from available weather data only. • Control-knowledge based feature to learn on-hours dynamic responses. • Multi-modal approach with eight day-type features to learn occupancy loads. • Deep recurrent learning and AutoML methods compared to the proposed method. [ABSTRACT FROM AUTHOR]

Representing building layouts as graphs can extract critical design patterns that would facilitate space syntax analyses as well as design mining and automation but traditional approaches (e.g., non-weighted adjacent graphs) encountered problems in modular buildings, as they are largely shaped under the principle of 'modularity' rather than freeform cast in-situ elements. This paper attempts to develop a novel analytical tool called ModularGraph to represent modular building layouts (MBLs) as graphs considering their unique adjacency, connectivity, and conjoint relationships in a triumvirate. It does so by developing a prototype then applying it to 36 modular buildings for iteration, finetuning, and finalizing. It is found that ModularGraph can effectively translate heterogeneous forms of MBLs into unified graph-based representations with rich graphic and semantic information. This study not only contributes an innovative graph analytic tool for design pattern mining, but also lays a stepping stone towards generative AI for modular building design. • Propose a graph triumvirate structure for modular building layout representation. • Incorporate a weight mechanism to indicate the strength of spatial relationships for better semantic interpretations. • Perform a quantitative analysis on the layouts of 36 modular buildings in Hong Kong using the proposed framework. • Uncover patterns in modular building layout designs exemplified by ModularGraph. • Develop a machine learning model to learn knowledge from layout designs represented by ModularGraph. [ABSTRACT FROM AUTHOR]

As the population and industries continue to gather in cities, such cities face acute shocks caused by various natural disasters and high pressure caused by human interference. The means of accurately assessing and improving the level of urban resilience (UR) to cope with disturbances and shocks, enhance regional resilience, and improve sustainable urban development has become a hot topic. In this study, we constructed an UR assessment framework using "social-economic-institutional-ecological-engineering" to explore the dynamic evolution of spatial and temporal patterns in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China, to reveal the main factors influencing the evolution of this spatial pattern and the strength and interaction mechanisms among such influencing factors and to dynamically simulate the spatial and temporal evolution characteristics in the next 16 years. The results show that from 2000 to 2019, the difference in UR level in the GBA is obvious. Hong Kong and Macao are obviously ahead of other cities, and the comprehensive resilience level of Guangzhou and Shenzhen cities in the mainland is developing rapidly. The difference in per capita consumption capacity, industrial structure optimization, foreign trade vitality, infrastructure support and other factors are the main causes of the spatial differentiation of UR in the GBA. In the future, the UR level of the GBA urban agglomeration will show an overall upwards trend. The three development poles of Guangzhou-Foshan, Shenzhen-Hong Kong, and Zhuhai-Macao have obvious advantages in spatial distribution. The results of the study can enrich regional UR research, and also provide theoretical references to facilitate the high-quality development of the area. [Display omitted] • We constructed a "social-economic-institutional-ecological-engineering" urban resilience assessment framework. • The paper developed an evaluation system for the urban resilience to reveal its spatial and temporal evolution patterns. • The main factors influencing the evolution of the spatial patterns of urban resilience is investigated. • Our results provide a basis for the development of comprehensive management framework for urban resilient. [ABSTRACT FROM AUTHOR]

The environmental performance of organizations is an increasing focus in cleaner production. This paper explores how the importance and performance of environmental practices were perceived among professional-level employees in Hong Kong, China. Based on a literature review on sustainable development and environmental management, we developed a structured questionnaire to measure respondents' perceptions towards environmental practices. Using responses from 348 professional-level employees in Hong Kong organizations, we employed importance-performance analysis for identifying some improvement opportunities. In addition, we applied exploratory factor analysis to identify the underlying environmental factors based on the importance ratings. Results of the study demonstrated that the performance of environmental practices was strongly associated with perceived importance of environmental practices. As environmental practices, it was found that Hong Kong organizations and employees primarily focused on saving paper and energy resources. However, they are not embracing the concept of green value chain and have yet to engage their suppliers to go green. This paper contributes to identify the key internal and external factors of environmental practices. [ABSTRACT FROM AUTHOR]

The approach of low or zero carbon building (L/ZCB) has attracted increasing attention in both academic and professional fields as the carbon emissions attributable to buildings kept increasing in the past decades. However, there exist challenges with modeling the carbon emissions of high-rise buildings in high-density urban environments. The aim of this paper is to examine the challenges and develop strategies for modeling carbon emissions in high-rise public residential buildings within the context of Hong Kong. The paper first reviews the challenges facing the modeling of the carbon emissions of high-rise buildings both generally and in Hong Kong, and examines their relevant implications for building design decision making. The approaches to establishing reference building models, e.g. example, real and theoretical reference building, are investigated drawing on the regulatory and practical guidance for carbon emission modeling in Hong Kong. The paper then develops a simulation approach to analyzing the obstacles to building energy modeling for typical high-rise public residential buildings in Hong Kong. Considering the urban environmental factors that may contribute to biased results for energy simulation, this paper is focused on the technical issues during the conversion of data from BIM model to energy simulation software. Thermal zones and user behavior are also addressed since technical and subjective assumptions could lead the simulation to a wrong direction. Understanding of such challenges enables the energy simulation to perform smoothly and also informs carbon emission modeling for high-rise L/ZCBs in other urban settings. [ABSTRACT FROM AUTHOR]

Low-carbon building (LCB) has been regarded as an innovative and practical approach to reducing building carbon emissions. The design decision-making for LCBs should consider various criteria which however are often associated with uncertain information. Little research has examined multi-criteria decision making (MCDM) in selecting LCB measures, particularly in high-density subtropical urban environments. That selection process is inhibited by the lack of consensus on assessing the performance of LCB options and of an efficient decision support system. The aim of this paper is to develop a BIM-integrated fuzzy MCDM model for selecting LCB measures. The paper identifies the key criteria and alternatives to systematically assess LCB measures. Five criteria and nine alternatives were identified within the context of high-rise commercial buildings in Hong Kong, which are centralized on technical, economic and environmental aspects of building performance. With the use of BIM and eQUEST, a MCDM model based on Fuzzy PROMETHEE is developed. The developed model is validated utilizing a real project case in Hong Kong. The results will provide design decision-makers with a consolidated tool for selecting LCB measures. [ABSTRACT FROM AUTHOR]

Energy consumption of lift systems is one key issue in modern high-rise buildings, drawing property owners' attention and accounting for 6% of total electricity consumption by end-use in Hong Kong. A Benchmarking Energy Performance Indicator (BEPI), , measured in J.kg−1.m−1 and proposed by the first author of this paper for lift installations is mentioned in the Technical Guidelines of the Building Energy Code , as one emerging good engineering practice. BEPI is a fair parameter for comparing energy performance of lifts irrespective of their brand, model, travel, speed, capacity and control. It considers energy performance due to both the motor drive efficiency and traffic control intelligence. However, one main obstacle to make it statutory is the lacking of a generic monitor able to retrieve three sets of real time data (normally unavailable on an existing lift) to compute the BEPI, namely energy consumption, instantaneous car load and traveling distance, and to collect ample data statistically reliable enough to determine an acceptable threshold value. This paper describes the development of a proof-of-concept prototype BEPI monitor by giving full technical details on the rationale and history of development, the hardware components, software framework, and updated numerical results of one implementation inside the headquarters of Electrical & Mechanical Services Department (EMSD) of HKSAR. Experiences in installing and calibrating those external sensors that make the whole system non-disturbing to normal lift operation, as well as the procedures in computing the BEPI, are discussed in greater details. It has been shown that the BEPI is traffic dependent but the weekly average of it is relatively stable, confirming it may be robust enough for benchmarking purpose. The solution described in this paper may help roll out the monitoring of BEPI for all lifts inside and outside Hong Kong. [ABSTRACT FROM AUTHOR]

Studying mobility patterns in public transport systems is critical for multiple applications from strategic planning to operations control to information provision. Unveiling and understanding the underlying (unobserved) mechanism governing the generation of (observed) mobility patterns are challenging. Considering the recurrent human travel activities and system operations, typical mobility regularities (or variations) patterns of the system can be captured by travel demand. This paper proposes a new paradigm to investigate the regularity in macroscopic mobility patterns for urban rail applications using concepts from image processing and pattern recognition to identify distinct demand patterns. We analyse the within-day demand patterns and day-to-day comparisons by constructing the spatiotemporal eigen-demand images (faces). The case study showed that the entry demand of Hong Kong metro network over 6 months can be grouped into 5 distinct clusters. This new perspective of eigen-demand allows examining the internal essence of large amounts of mobility patterns over time and reveals a global daily demand pattern at the entire system. [ABSTRACT FROM AUTHOR]

• A big data computational text analysis based on a corpus of 2.4 million words. • Comparison of major themes on air pollution in stakeholder discourse in Hong Kong. • Three stakeholder groups are studied; all focus on emissions and pollution control. • Public health is a greater concern in MEDIA compared with other groups. • More personalized health information to be shared with the vulnerable groups. Stakeholder engagement is critical to the successful formulation and implementation of environmental policies. Text analysis can serve as an important means to decipher stakeholder (dis)agreements. Traditionally, researchers analyze texts using qualitative text analysis. Relying only on qualitative text analysis can no longer be sufficient to handle very large amounts of textual data. Now computational methods can be applied to help extract opinions in electronic texts. Our paper adopts a big data computational text analysis approach (keyword analysis, keyword co-occurrence, thematic analysis), based on a corpus of 2.4 million words, to compare concerns towards air pollution among three stakeholder groups (i.e. the government (GOV), the environmental groups (NGO) and the news media (MEDIA)) in Hong Kong, between 2002 and 2012, a period when air pollution was subject to rigorous policy debates and discussions. Our analysis shows the somewhat different concerns of the stakeholders. The stakeholders focus heavily on emissions and end-of-pipe pollution control. Though the advocation of sustainability since 1990s, the government-led command-and-control approach still dictates the discourse. Sustainability is featured more intensively by the Hong Kong Special Administrative Region (HKSAR) Government. Transboundary pollution (e.g. from Guangdong, China) is not a major concern for all stakeholder groups. Public health is a greater concern in MEDIA, as compared to the other two stakeholder groups. Future air pollution policy-making may direct more of its attention to the pressing concerns over the negative impacts of air pollution on health and its associated costs, with health experts getting more closely involved in the regulatory decision-makings. More information should be given to vulnerable groups, such as young children or workers in polluted environments. To better relate differential health risks of pollution in everyday life, both local and international governments should consider developing more personalized air pollution monitoring and health management systems for their citizens in future. [ABSTRACT FROM AUTHOR]

• Developing a new probabilistic model for service life prediction and revealing the probability distribution. • Newly constructing the probabilistic model of chloride diffusion coefficient based on mesoscopic concrete. • Comprehensively and quantitatively identifying the sensitivity of reliability index to multiple factors. • Proposing some anti-corrosion countermeasures in conjunction with the engineering practice based on the research results. Chloride attack is the primary cause of performance deterioration and life attenuation of reinforced concrete (RC) structures in marine environments. In an attempt to accurately predict the reliability and service life of RC structures under the co-effects of multiple factors, a comprehensively modified chloride-transport-based model is proposed in this paper. Based on Fick's second law, a multifactor integrated deterministic chloride transport model is developed considering the time dependence, concrete mix proportion, chloride binding capacity, freeze–thaw cycles, sustained load, temperature, humidity and concrete deterioration. Based on extensive literature review combined with the results of multitudinous long-term field exposure tests used in the durability design of Hong Kong-Zhuhai-Macao Bridge and Shenzhen-Zhongshan Bridge, the probability distribution types and parameter values of the governing variables are determined. Taking Qingdao Bay Bridge as an example, the time-variant reliability index, failure probability and reliability-index-based corrosion initiation are determined by using the equivalent normalization method (JC method) and Monte Carlo simulation technique for different environmental zones including atmospheric/splash/tidal/submerged zones. The sensitivity of the reliability index to the control variables and the effects of age index, chloride binding capacity, numbers of freeze–thaw cycles, stress level and concrete deterioration on the reliability index are quantitatively investigated. The results show that the time-variant reliability of different environmental zones is sequenced as: atmospheric zone > submerged zone > tidal zone > splash zone; the sensitivity of reliability to the governing variables sequenced as: concrete cover thickness > surface chloride concentration > chloride diffusion coefficient > critical chloride concentration; the time dependence of the diffusion coefficient has a significant effect on the time to corrosion initiation and cannot be ignored in the predictive model for both the high-performance or ordinary concrete; the number of freeze–thaw cycles and the tensile stress level are relatively insensitive but substantially detrimental to the reliability of corrosion initiation. [ABSTRACT FROM AUTHOR]

Multipath and non-light-of-sight (NLOS) reception greatly deteriorate the GNSS positioning accuracy in urban areas. Currently, most of the attempts using machine learning in this area focus on signal status prediction (LOS, multipath, NLOS). This paper exploits the capability of deep learning in multipath/NLOS mitigation. A new input feature, the single-differenced residual map is proposed, which has a high correlation with the user location and is very effective in multipath/NLOS mitigation. Combining the domain knowledge in GNSS, features of residual maps from different satellites are extracted by the proposed network and generate the heat map to indicate the user location. The proposed network can significantly improve the positioning accuracy of 84% of the epochs in the dense urban to 5-meter level. In addition, our network has a superior generalization ability, reducing the error of 90% of the epochs to 7 m level in a new scenario. • A deep learning network structure to directly estimate urban GNSS positioning. • A new GNSS feature, single-differenced residual maps, is proposed to improve the positioning accuracy of the neural network. • The proposed network is validated and tested using real GNSS raw data collected in urban canyons at Hong Kong. [ABSTRACT FROM AUTHOR]

The construction industry has been focused on sustainability, particularly with regards to reducing CO 2 emissions and recycling construction and demolition (C&D) waste. This study focuses on the alternative technology adaptation of carbonized pavement compact production by using waste concrete powder (WCP) which can be a substitute material to concrete and also able to absorb CO 2. While material scientists embraced and developed this technological application, the financial perspective for adopting this technology has yet to be properly addressed. This paper conducts a feasibility assessment, which includes technical, environmental, social, and financial factors, from different stakeholders' perspectives (government, construction contractors, and material manufacturers) to launch the production of carbonized pavement compact by utilizing WCP. The benefit-cost analysis underlies the Evolutionary Game Model functions' formulation, which emphasizes not only the obvious financial benefits from WCP or its carbonized compacts sale but the benefits from the absorption of CO 2 during the compacts production and avoiding WCP disposal at a landfill. The results based on a Hong Kong case (typical multistorey apartment building) identify promising scenarios where a minimum of 2300t of WCP is required for stakeholder interest in recycling, and a WCP wholesale price of 150HKD/t is suitable for the C&D contractor to participate in the recycling market. The study also estimates a cost-effective selling price of finished carbonized WCP compacts, which is competitive with similar products on the market. Important insights are drawn to initiate the WCP market and consequently increase the sustainability of the C&D recycling market. [Display omitted] • Providing a solution for reducing CO 2 emissions during pavements production. • Assessing the feasibility of launching carbonized WCP pavement compact market. • Considering technical, environmental, social, and financial factors for assessment. • Obtaining feasible conditions for carbonized pavement compact production from WCP. [ABSTRACT FROM AUTHOR]

Modular integrated construction (MiC) has received remarkable attention for enhancing the productivity performance of delivering housing projects in densely populated cities such as Hong Kong. MiC projects suffer from unique risk factors compared with traditional construction methods. Previous studies have mainly focused on the direct linear impacts of risk factors and how they may affect project success. However, the MiC supply chain involves many stakeholders with high interdependency. How the risks are interconnected and interact with different stakeholders is a crucial issue to be analyzed and addressed. This paper deploys a social network analysis (SNA) method to identify and decipher stakeholder-associated productivity performance risks (PPRs) and their interrelations in an MiC project in Hong Kong. Fifteen critical PPRs and twelve essential interactions were demonstrated by simulating the complex network of the target project. Research findings show that inadequate project planning and scheduling has the greatest influence on collaborative decision-making support; Delayed assembly schedule and delayed delivery of modules also exert considerable influence on project planning and scheduling; The main contractor plays a leading role as a coordinator in the whole MiC process. The research further identifies several primary challenges, including the inefficient data capture approach, insufficient supply chain planning and progress monitoring, poor communication and information interchange among project stakeholders, and lack of collaborative decision-making support. This is the first study that dynamically examines and demystifies stakeholder-associated PPRs embedded in MiC projects in Hong Kong on a network basis, which could assist researchers and construction professionals in perceiving, investigating, addressing, and mitigating these risks in an effective and efficient approach. [ABSTRACT FROM AUTHOR]

Abstract: Prefabrication has been increasingly used in buildings. It is recognised as a solution to reduce waste arising during design and construction phases. However, there is little emphasis on life cycle design issues for prefabricated buildings located in dense high-rise building environments. The purpose of this paper is to review the application and identify benefits and impediments of design for deconstruction and Industrialised, Flexible and Demountable building systems when applied to precast concrete construction. The paper presents the results of a comprehensive literature review, and two case studies of recently completed institutional buildings using prefabrication. The literature review shows that, so far, design for deconstruction is not a common practice in the building industry. The case studies showed some limitations such as the dense urban environment conditions and limited site area. The promotion of a closed-loop material cycle is critical to contribute to sustainability thus minimising CO2 emissions, natural resources consumption. [Copyright &y& Elsevier]

Carbon emission trading mechanism is an important market-based instrument to address global climate change. The auction ratio and price of carbon emission allowances (CEA) are cores of the carbon emission trading mechanism. What combination of CEA auction ratio and auction price is most conducive to carbon emission reduction for emission control enterprises? There are still relatively few studies conducted on this issue, and there is no clear answer from the views of theory and practice. In this paper, the AIM/Enduse model was used to analyze the changes and differences of installed power capacity, power supply, energy consumption and carbon emissions in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) with different combinations of CEA auction ratios and prices. Moreover, the best pathway of energy transition was explored in the power industry of the GBA, and the best combination of CEA auction ratios and prices was identified in the GBA. The results show that: (1)The carbon emission constraint starts to work only when the auction ratio of CEA is increased to 50% and the auction price is increased to 60 CNY/ton (Scenario p 3). When the auction ratio of CEA is 100% and the auction price reaches 120 CNY/ton (Scenario p 5), a low-carbon transition of the power sector in the GBA can be achieved. (2) Under scenario p 5 , the total cost of power transition rises and then falls. And the cost of carbon in the power sector increases exponentially as the auction ratio of CEA and the auction price rise. However, the growth in the cost of power supply is relatively flat, which shows that appropriate carbon trading mechanism can improve the economic benefits of power sectors. With the increase of installed capacity of clean low-carbon energy generation and power supply, as well as the decrease of local power cost in the GBA, the proportion of outsourcing power can be appropriately reduced in the future, with an aim to reduce the external dependence of electricity to ensure the security of energy supply. In the end, it suggests that cities in the GBA should give full play to their regional advantages and establish a unified carbon emission trading market in the GBA as soon as possible. This study provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. • What is the best combinations of CEA auction ratios and auction prices in the GBA? This paper gives a clear answer. • The best transition pathway of the power industry under technological progress and carbon trading policy was suggested. • With the decrease of local power cost, the proportion of outsourcing power can be appropriately reduced in the future. • Provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. [ABSTRACT FROM AUTHOR]

Abstract: In several sign languages, it is observed that sometimes a nominal expression appears twice within the same sentence, once in its regular syntactic position and once sentence-finally as a pronominal pointing sign. This paper investigates how these sentence-final pronouns are used in Hong Kong Sign Language (HKSL), which is the natural sign language used by the Deaf community in Hong Kong. Previous studies of sentence-final pronouns in sign languages put forward three major accounts: these pronouns serve as focus/emphasis markers, agreement markers, and right dislocations. On the basis of elicited and spontaneous discourse data collected from deaf native signers, this paper argues that sentence-final pronouns in HKSL are right dislocated ‘aboutness’ topics. Given that pronouns in HKSL, as in other sign languages, are directed towards the locations associated with the intended referents, sentence-final pronouns can help secure the attention of the addressee towards the topics in discourse by upholding their visual prominence via spatial indexing. This strategy is most commonly used in conversational interactions. [Copyright &y& Elsevier]

As the consumption of electricity increases, air pollutants from power generation increase. In metropolitans such as Hong Kong and other Asian cities, the surge of electricity consumption has been phenomenal over the past decades. This paper presents a historical review about electricity consumption, population, and change in economic structure in Hong Kong. It is hypothesized that the growth of electricity consumption and change in gross domestic product can be modeled by 4-parameter logistic functions. The accuracy of the functions was assessed by Pearson's correlation coefficient, mean absolute percent error, and root mean squared percent error. The paper also applies the life cycle approach to determine carbon dioxide, methane, nitrous oxide, sulfur dioxide, and nitrogen oxide emissions for the electricity consumption of Hong Kong. Monte Carlo simulations were applied to determine the confidence intervals of pollutant emissions. The implications of importing more nuclear power are discussed. [Copyright &y& Elsevier]

• A new concept and feature of grid-responsive building and the needs are presented. • Opportunities/challenges for buildings to provide ancillary services are presented. • Applications/methods for HVAC systems to provide ancillary services are investigated. • Potential capacities of HVAC systems to provide ancillary services are quantified. Renewable electricity generations have been growing rapidly in recent years worldwide as a result of efforts to address the global energy issue. However, it has also imposed increasing challenges on the balance of power grids due to their intermittent nature. Building sector, as the largest consumer, is expected increasingly to play an important role in providing ancillary services (AS) to relieve stress and reduce the needs of investment for power balance of the smart grids. Grid-responsive building therefore becomes a worthwhile and essential feature of buildings today and in the future. This paper provides an overview of the classification, benefits, applications as well as methods/technologies for HVAC systems in non-residential buildings to provide ancillary services, as fast responses (i.e., in the magnitude of seconds or minutes) to the needs of smart grids. In addition, the challenges of applications and potential solutions are investigated and summarized. The potential capacities of HVAC systems in the entire non-residential building sector in Hong Kong for providing frequency regulation (FR) and spinning reserve are also quantified. [ABSTRACT FROM AUTHOR]

The use of structural steelwork (SS) for buildings continues to grow worldwide owing to its sustainability benefits. However, the market share of SS in the building sector of Hong Kong greatly lags behind other markets. This paper focuses on providing a comprehensive understanding of the issues that greatly drive or inhibit SS adoption in Hong Kong from a project lifecycle perspective. The methodology encompasses both qualitative and quantitative approaches. Semi-structured interviews were conducted with 28 professionals from developer, structural engineering consultant, main contractor, steel specialist contractor, and steel stockholder companies. The results identified 12 driving factors and 25 barriers affecting SS adoption in Hong Kong. A questionnaire survey with 118 practitioners was carried out to identify the most important driving factors and barriers. The results revealed that "increased speed of construction" and "must-have requirements" were the two most important driving factors; while "shortage of skilled labor", "shortage of supervisors working directly under main contractors", "high construction costs", "shortage of experienced designers and draughtsmen", and "lack of education, training, and design experience on structural steelwork" were the five most critical barriers. This may imply that education and training are needed to improve knowledge and skills of professionals and workers, and thus to ensure an adequate supply of manpower. The findings of this study not only contribute to the existing body of knowledge on SS practices but also provide valuable references for helping practitioners and policymakers to promote sustainable construction methods within the building sector. • Increased speed of construction and must-have requirements are important drivers. • Manpower shortages in the design and construction phases are critical barriers. • High construction cost also inhibits the use of structural steelwork. [ABSTRACT FROM AUTHOR]

Our paper explores if Hong Kong public universities take advantage of the current information and communication technologies (ICT) for online social responsibility (SR) reporting. Content analysis of the university website was the principal method for data collection. The results indicate that Hong Kong Universities assign great importance to SR, and generally perform well for online SR reporting through the application of ICT, in terms of varied "perspectives" and "items". This study is exploratory in nature, and makes contributions to the existing literature. [ABSTRACT FROM AUTHOR]

Abstract: By means of computational fluid dynamic (CFD) simulations, this paper investigated how rural winds transport relatively clean air into high-rise urban areas to dilute airborne pollutants. Two ventilation concepts for indoor environments were applied: the age of air to quantify the time taken by rural young air to reach a given place after it enters an urban area and the air exchange efficiency to evaluate the efficiency of rural winds flushing the entire urban canopy layer. Several square building arrays with street aspect ratios (building height/street width, H/W) ranging from 1.5 to 5.3 and building area densities of 0.25 (medium) or 0.4 (compact) were considered as the approaching wind is parallel to the main street whose length varies from street scales to neighborhood scales (330–510 m to 1.03–1.65 km in full-scale). Results show that considerable young rural air enters windward entries but a major fraction of air is vertically driven out as flowing deeper into such high-rise building arrays. So air exchange efficiencies are less than 50% in street-scale arrays, and smaller in longer (neighborhood-scale) or narrower arrays. For the neighborhood-scale medium arrays, considering the power-law velocity profile in the upstream free flow, a taller array gains a larger inflow rate across its windward entry and experiences younger air and greater air exchange efficiency than a lower one. If all buildings are theoretically open-based in a neighborhood-scale compact array, air becomes much younger everywhere and the air exchange efficiency doubles. In arrays of buildings with different heights, the secondary streets in front of taller buildings get younger air due to the downward flows within them. Although further investigations are still required before providing a practical framework, this paper is one of the first attempts to find ways in improving the ventilation performance in high-rise cities like Hong Kong. [Copyright &y& Elsevier]